AGA自适应加速遗传算法

AGA自适应加速遗传算法，适用于机器学习算法中AGA自适应加速遗传算法，适用于机器学习算法AGA自适应加速遗传算法，适用于机器学习算法

clc;
clear;
figure（8）;
par=zeros（1100）;
par2=zeros（1100）;
time=zeros（1100）;
sstep=zeros（1100）;

for j=1:1
    disp（‘------------------------------------------------------------------‘）;
    episodes=100;  
    theta=zeros（541）;
    distance=0;
    v=zeros（271）;
    gamma=0.9;
    lambda=0.5;
    epsilon=10^（-20）;
%   F=400*eye（10）;
    pend_actions=2;
    for r=1:episodes
        disp（‘%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%‘）;
        noise=（2*rand（13）‘-1）.*[2;2;0];%初始化状态
        state=[140;0;0]+0*noise;  
        z=zeros（271）;
        step=0;
        signal=0;
        endsim=0;
        mytime=cputime;
        
        while  endsim==0
            step=step+1;
            phi=computphi（state）;
            phi_sa=zeros（542）;
            for i=1:pend_actions
                phi_sa（:i）=[phi.*（i==1）;phi.*（i==2）];
            end
            pi=computpi（phi_satheta）;
            psi=computpsi（phi_sapi）;
            action=select（pi）;%take an action
            disp（‘the action is‘）;
            disp（action）;
%           disp（pi0）;
%           disp（‘action=‘）
%           disp（action）;

            [nexts reward endsim] = simulator（stateaction）;
%             disp（‘nexts=‘）;
%             disp（nexts）;
%             disp（‘reward=‘）;
%             disp（reward）;
%             disp（‘endsim=‘）;
%             disp（endsim）;
            plot（nexts（31）nexts（11）‘o‘）;
            hold on;
            phi2=computphi（nexts）;
            state=nexts;
            
            z=gamma*lambda*z+phi; %更新适合度轨迹
%     
%           K=F*z/（1+（phi‘-gamma*phi2‘）*F*z）;
%           v=v+K*（reward-（phi‘-gamma*phi2‘）*v）;
%           F=F-F*z*（phi‘-gamma*phi2‘）*F/（1+（phi‘-gamma*phi2‘）*F*z）;
            alpha=0.5;
            beta=0.2;
%             alpha=20/（50+step）;
%             beta=1/（25+step）;
            delta=reward+gamma*phi2‘*v-phi‘*v;
            v=v+alpha*delta*z;
            theta2=theta+beta*delta*psi（:action）;
    
            t=theta2-theta;
            theta=theta2;
            distance=norm（t2）;
            if distance>0&&distance%                 signal=1;
                break;
            end
    
%             if j>0||step>1000
%                 signal=1;
%             end
            
        end
        time（jr）=（cputime-mytime）/step;
        sstep（jr）=step;
%         disp（‘episode=‘）;
%         disp（r）;
%         disp（‘endsim=‘）;
%         disp（endsim）;
        disp（‘step=‘）;
        disp（step）;
        
        
        % [sterew]=evaluate（theta）;
        % par（jr）=ste;
        % disp（‘step2=‘）;
        % disp（ste）;
    end
    [steprew]=evaluate（theta）;
end

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----

     文件       2765  2014-04-26 19:48  example\AC.asv

     文件       2776  2014-04-27 20:36  example\AC.m

     文件        414  2014-04-25 11:11  example\computphi.asv

     文件        420  2014-04-26 16:11  example\computphi.m

     文件        214  2014-04-25 17:38  example\computpi.m

     文件        214  2014-04-18 16:32  example\computpsi.m

     文件        691  2014-04-26 20:00  example\evaluate.m

     文件        140  2014-04-25 23:05  example\select.m

     文件        512  2014-04-26 00:11  example\simulator.asv

     文件        517  2014-04-27 20:51  example\simulator.m

     目录          0  2014-04-26 22:20  example

----------- ---------  ---------- -----  ----

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